crm systems and sales force automation

CRM Workflow Automation + Augmented Intelligence Drive Sales Force Efficiency

The explosion of CRM platforms and associated integrations primes the business domain for Sales Force Automation – a big topic (next to big data) which accommodates all end user sets and operating models. Whilst I am a fan of configuring automation tools in the organisational context that improves sales-team intelligence; true CRM deployments will harness distributed intelligence and position the human capital within the interlocking circles of people and technology. Here, the challenge is to configure CRM workflows, modules and processes around heterogeneous sales force constituents where individuals all have their own unique way of addressing the front line (yet are congruent and aligned against the enterprise vision). Additionally, your contact tracking system needs to provide value laden insights into prospect behaviour across your distribution channels to enable retargeting and conversion rate optimisation. The CRM system in its own right needs to be like a series of lanes on highway, slow, fast and just ‘going with the flow’. It needs to be malleable so that when you need to intervene when things are not going right; you can do so with agility and the resulting user adoption is fluid (not sticky). As a matter of personal choice and being heretic like against the heavy weights like SalesForce, I am an evangelist of Zoho CRM; deploying most of its features to bridge the digital divide that exited in my business when we took it over.

Within my own commercial context at Hideaway Holidays (South Pacific Destination Specialist Wholesalers), the CRM system we use is configured in a manner that allows the front line team to asses and fully qualify leads in the first instance. Enquiry forms are web-hooked into the CRM system as we discovered that there are specific data-points that we need to fully capture in order for a lead to be effectively ‘qualified. This, coupled with insights into prospect behaviour on our semi-dynamic (current) website lead to the introduction of Alex – an enquiry handler Q and A chatbot that is triggered on contextual attributes (user defined) such as time spent on site, landing page and current page URL. Here, we are effectively automating the lead capture process by invoking an engaging conversation in a simple to type and click interface that not only enthuses the prospect but ensures our sales team are working with qualified leads in totality. From here, various rules and layouts are configured to ensure that the salesforce is fully aware of not only time of initial enquiry but also value laden insights into visitor behaviour on our website including pages they looked at, where they came from, device information and actions performed on pages. Whilst this is out of the box functionality and might seem rudimentary in the context of ‘knowing your customer’; it is actually an application of augmented intelligence because we are using technological tools to garner data on prospect behaviour, thereby future proofing any chance of rejection. The lead to deal conversion process in the business is built on simple application of deal stages that segment the various stages of the sales cycle. This, in combination with contact level tracking that logs and timestamps visits to the website (actions performed, duration on site, pages visited) amplifies our ability in controlling opportunity management. Altogether, the CRM cycle then feeds back into an iterative marketing process wherein we are scoping how to re-target visiting customers or those that are already in the pipeline (existing potentials as they say in the CRM terminology).

At its most fundamental level, the CRM is used to field and track the heavy pipeline of thirty plus enquiries that we receive a day; on the back of 600-800 visitors a day of which 84% a new and majority from Google Organic Search.

Mohit (Max) Bhanabhai – Executive Director (TravelBiz Pty Ltd)

Whilst it’s true that augmented intelligence demands data and qualitative insights via technology; the onus is on the human capital process to interpret, extrapolate and act on this information. Internally, we have inter-module reports that can be run against a series of data points to provide insights into prospect behaviour and where the potential exists in the sales pipeline. For example, we can track the last time a deal (potential) was updated to a respective stage whilst concurrently checking if the contact has come back to our website and checked out other associated pages. In the wholesale tourism business, this is paramount as it glues together a unique portrait of your prospects journey, allowing the front line team to take this as sanctified data and re-deploy their offering accordingly.

Zoho CRM is a beast of a system and I have configured it in a manner that doesn’t depend on strong user adoption curves (even a monkey can use it). Anyone exposed to spreadsheets, customer record systems, business applications or simple access like databases would see my implementation of the CRM system as value added and intuitive. I whole heartedly commend Zoho CRM for allowing enterprises of all sizes to configure, customise and scale business intelligence to drive measurable and actionable insights in the customer service and sales cycle.

2 thoughts on “CRM Workflow Automation + Augmented Intelligence Drive Sales Force Efficiency

  1. XMC.pl

    Sick! Just acquired a brand-new Pearl and I can now read your blog on my phone’s browser, it didn’t do the job on my previous 1.

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